Top Echelon
ESSENTIAL RESPONSIBILITIES
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Own the full ML research lifecycle: problem formulation, experimentation, model training, evaluation, optimization, and deployment.
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Design and improve state-of-the-art Computer Vision and Document AI models for parsing and understanding unstructured enterprise data.
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Lead architectural improvements to vision models and VLM-based document understanding systems.
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Build scalable data pipelines and evaluation frameworks to continuously measure and improve performance.
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Transition research prototypes into reliable, production-grade systems in collaboration with engineering.
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Establish best practices for experimentation, reproducibility, benchmarking, and iteration.
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Work directly with founders to shape product direction and long-term technical strategy.
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Contribute to research credibility through publications, benchmarks, or open contributions when appropriate.
QUALIFICATIONS
Education
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Master’s or PhD in Computer Science, Computer Vision, Document AI, or a closely related field from a top-tier institution.
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Strong academic research background with multiple publications in relevant areas preferred.
Experience
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Up to 6 years of experience post–Master’s or PhD.
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Proven experience owning end-to-end ML research initiatives.
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Experience in a 0-to-1 startup environment with high ambiguity and rapid iteration.
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Background at a leading research lab (e.g., DeepMind, FAIR, Microsoft Research, OpenAI, Anthropic) strongly preferred.
Technical Skills
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Deep expertise in Computer Vision, Document AI, multimodal learning, or related domains.
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Experience building or significantly improving model architectures.
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Experience working with smaller foundation models (e.g., 3B–7B parameter range).
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Strong Python proficiency and familiarity with modern ML frameworks.
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Experience training and deploying models for parsing and understanding unstructured data.
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Hands-on experience building evaluation pipelines and integrating models into production systems.
Soft Skills
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Comfortable moving between theory, experimentation, and production deployment.
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Strong product intuition and ability to prioritize research with business impact.
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High ownership mindset and bias toward action.
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Willingness to work in person and commit to the intensity of an early-stage company.
IDEAL CANDIDATE PROFILE
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Has built or materially improved document layout models or vision-language systems.
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Demonstrates architectural depth beyond fine-tuning existing models.
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Thrives in fast-paced environments with minimal process.
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Motivated by building category-defining infrastructure from the ground up.
WORK ENVIRONMENT
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In-person role based in San Francisco, CA.
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Fast-moving startup environment with high ownership and accountability.
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Flexible hours with potential for extended work periods during high-demand cycles.
COMPENSATION & BENEFITS
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Competitive base salary: $200K–$300K
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Meaningful equity ownership: 0.1%–1%
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Visa sponsorship available for exceptional candidates (including new H1B applications).
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Opportunity to shape the technical foundation of a high-growth AI company.
INTERVIEW PROCESS
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30-minute call with Co-Founder
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Paid remote or in-person work trial (up to one week, asynchronous)
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Offer decision
